Tuning order configurator performance by dynamic integration of manufacturing and field feedback

ABSTRACT

A novel and non-obvious method, system and apparatus for tuning order configurator performance by dynamic integration of manufacturing and field feedback information. A method for dynamically tuning order configurator behavior by using product issue data can include collecting product issue data for a manufactured product, the product issue data including performance and attribute information of a part of the manufactured product, analyzing the collected product issue data to identify a problematic part, and, modifying the order configurator using the analyzed product issue data.

BACKGROUND OF THE INVENTION

1. Statement of the Technical Field

The present invention relates to integrated supply chain systems andmore particularly to tuning order configurator performance by dynamicintegration of manufacturing and field feedback information.

2. Description of the Related Art

Generally, in integrated supply chain manufacturing systems, customersplace product orders via a user interface, e.g., via a computer incommunication with the Internet. The generation of valid orders is themain objective of an “order configurator” (also called a salesconfigurator.) Typical order configurators use a set of product offeringrules that specify and validate the various factors of part/componentcombinations such as compatibility, min-max values, pre-requirements,co-requisites, component capacity, and the like. Product engineers andmarketing personal typically will prescribe the relationships betweendifferent parts and the rules that govern the selections of these parts.The rules are updated to reflect upcoming product announcements,production needs, and corrections. However, during the delay before theissuance of the updated rules, the order configurator can generateorders containing parts that are failing in manufacturing or the field.

Failing parts in manufacturing are encountered, typically, during thetesting phase of the product. Failing parts in the field are typicallyencountered when the product is shipped and installed at the customersite and the field. Reliability and availability issues includingcomponent fault and performance degradation are often reported throughthe service mechanisms after a system has been installed and activated.Unchecked these problems may cause deterioration in customersatisfaction, rework of installed systems, increased maintenanceexpenses, and loss of business.

Current systems are human-based, manual processes where manufacturingand field failure information are used to manually review the currentconfiguration rules, e.g., from announcement letters and data templates,to determine which rules need to be changed or added. Often new rulesare created and added instead of modifying existing configuration rules.Typically, order configurator product modelers will use modeling logicto implement any new rules. Issues with current systems include beingmanual, unreliable, inefficient, and rather slow. For example, it maytake several months before the manufacturing and field failureinformation are used to modify the order configuration rules (if theyare used at all).

Current methods do not offer dynamically integrated manufacturing andfield feedback to effectively optimize or tune an order configuratorbased on reported manufacturing and field failure data. Accordingly, thecurrent order configurators will continue to configure orders withnon-reliable parts and/or part combinations. Additionally, with currentmethods, there is a lack of automatic modification of the existingconfigurator rules. However, adding new configuration rules to the orderconfigurator can continuously increase the size of the orderconfiguration bucket.

SUMMARY OF THE INVENTION

The present invention addresses the deficiencies of the art with respectto order configurators, and provides a novel and non-obvious method,system and apparatus for tuning order configurator performance bydynamic integration of manufacturing and field feedback information. Inone embodiment of the invention, a method for dynamically tuning orderconfigurator behavior by using product issue data can be provided. Themethod can include collecting product issue data for a manufacturedproduct, the product issue data including performance and attributeinformation of a part of the manufactured product, analyzing thecollected product issue data to identify a problematic part, and,modifying the order configurator using the analyzed product issue dataso as to avoid configuring the problematic/defective parts.

In another preferred embodiment of the invention, a product issues dataprocessing system can be provided. The system can include a productissues data store, a product issues analysis module coupled to theproduct issues data store, an automated product issues feedback enginecoupled to the product issues analysis module, the product issuesfeedback engine comprising program code enabled to collect productissues data for a manufactured product, the product issues dataassociating characteristics of the manufactured product determined tohave issues during manufacturing and field deployment, to modify anexisting configuration order for the manufactured product to account forthe characteristics in the collected product issues data.

In yet another embodiment, the automated product issues feedback enginefurther includes product issues analysis object information, a partsselection rule modifier coupled to the product issues analysis objectinformation, and an optimized order configurator coupled to the partsselection rule modifier, the configurator comprising rules for partsselection and parts object information.

Additional aspects of the invention will be set forth in part in thedescription which follows, and in part will be obvious from thedescription, or may be learned by practice of the invention. The aspectsof the invention will be realized and attained by means of the elementsand combinations particularly pointed out in the appended claims. It isto be understood that both the foregoing general description and thefollowing detailed description are exemplary and explanatory only andare not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute partof this specification, illustrate embodiments of the invention andtogether with the description, serve to explain the principles of theinvention. The embodiments illustrated herein are presently preferred,it being understood, however, that the invention is not limited to theprecise arrangements and instrumentalities shown, wherein:

FIG. 1 is a pictorial illustration of a manufacturing supply chainnetwork incorporating a dynamic manufacturing and field issues feedbackengine;

FIG. 2 is a flowchart illustrating a process for dynamic manufacturingand field issues feedback in a manufacturing supply chain process;

FIG. 3 is a schematic illustration of dynamic manufacturing and fieldissues feedback engine;

FIG. 4 is a schematic illustration of the dynamic manufacturing andfield issues feedback engine incorporating an optimized orderconfigurator of FIG. 3;

FIG. 5 is a block diagram illustrating attributes of the parts objectinformation and manufacturing and field issues object information inFIG. 4;

FIG. 6 is a table containing examples of generic rules used to modifyorder configuration rules; and

FIG. 7 is a flowchart illustrating a process for the parts selectionrule modifier using the dynamic manufacturing and field issues feedback.

DETAILED DESCRIPTION OF THE INVENTION

Embodiments of the present invention provide a method, system andcomputer program product for optimizing and tuning of an orderconfigurator by dynamic integration of product issues, e.g.,manufacturing and field issues, feedback. In an embodiment of theinvention, product issues data associating characteristics of amanufactured product determined to have operation issues duringmanufacturing and/or in the field can be collected. The collectedproduct issues can be analyzed. Based on the product issues, e.g.,manufacturing and field issues, analysis, a part selection(configuration) for the manufactured product can be modified to accountfor the characteristics in the collected product issues data. Forexample, product issues data such as an error code specifying a rootcause, such as a failed part, for a failure exhibited in a product canbe applied to modify or tune an order configurator. Thereafter, theproduct issues data can be applied to an order selection to account forcharacteristics associated with the collected product issues data bymodifying the configuration rules. In addition, the product issues datacan be applied to an order selection to account for characteristicsassociated with the collected product issues data by modifying therelevant attributes of the parts so that the next time the configurationrules are performed, the non-reliable parts and part combinations areappropriately removed or “discouraged” from future selection.

In illustration, FIG. 1 is a pictorial illustration of a manufacturingsupply chain network incorporating a dynamic manufacturing and fieldfailure feedback engine. When a product 120 is manufactured, relatedmanufacturing failure data regarding issues arising during manufacturing110 of the product can be reported and stored in a manufacturing andfield failure data store 140. Such manufacturing issues can be detectedand defective parts will be replaced prior to shipping. Themanufacturing failure data can be fed back to alter the behavior of theorder configurator to not specify the defective part. Similarly, when aproduct 120 is shipped to a customer 130, related field issue dataregarding issues arising in the field with the product also can bereported and stored in a manufacturing and field issues data store 140.During the order configuration development process, the manufacturingand field issues feedback engine 150 can analyze the type of issue orfailure, determine characteristics of issue that reflect a root cause ofthe issue, dynamically modify the product configuration orders toremove, replace or adjust the non-reliable parts and/or productcombinations to provide an optimized parts selection order configurator.The optimized configured product order 160 can be sent to themanufacturing facility for manufacturing and testing 170 and thefeedback cycle from the manufacturing and field issues can be repeatedagain.

In further illustration of a manufacturing and field failure feedbackengine, FIG. 2 is a flowchart illustrating a process for dynamicmanufacturing and field issues feedback in a manufacturing supply chainprocess. A product can include a manufactured product component used inassembling a manufactured product. The manufacturing and field issuesengine 210 can be invoked during the order configuration developmentprocess. The manufacturing and field issues feedback are used to updatethe rules that select the parts for a manufactured product.

The updates may occur offline. In block 220 the parts order can beconfigured along with fulfilling the product order 230. In block 240,the manufacturing product can be tested beforehand and the productmanufactured and tested again afterwards. Any manufacturing issuesarising during the manufacture and test of block 240 can be reporteddirectly to the manufacturing and field issues engine 210 or can bestored in the manufacturing and field issues storage 140. In block 250the manufactured and tested product can be shipped 250 to the customer.After installing the product in block 260, the field failure issues canbe reported 270. In block 280 the product can be developed and the fieldissues can be analyzed in block 290. The feedback analysis can be usedto update configurator rules that select parts as well as given to aproduct development group. Once the manufacturing and field issues aredetermined, they can be fed into the dynamic manufacturing and fieldissues feedback engine.

In yet further illustration, FIG. 3 is a schematic illustration of adynamic manufacturing and field issues feedback engine 150. The dynamicmanufacturing and field issues feedback engine 150 can include theoptimized configurator 320, the parts selection rule modifier 330 andthe manufacturing and field issues analysis object information 340. Thedynamic manufacturing and field issues feedback engine 150 can havecomputer code enabled to analyze the product configuration orders andmodify them with new attributes responsive to manufacturing and fieldissues feedback.

The manufacturing and field issue analysis object information 340 can bea collection of observed or reported product issues as well as rootcause analysis information represented in a form such as the form shownin FIG. 5. The parts selection rule modifier 330 can incorporate themanufacturing and field issue analysis object information 340 and candynamically change the priorities of parts, the applicability status ofparts, and selectively enable or disable certain parts configuration.Additionally, the parts selection rule modifier 330 can change theassociation between a particular part selected to a product order. Theparts selection rule modifier 330 can have necessary logic to relate theissues analysis object information to part object information andassociated parts selection rules. The optimized configurator 320 canincorporate the dynamic feedback received from the parts selection rulemodifier 330 in order to fine-tune the rules that generate manufacturingparts selection.

In further illustration, FIG. 4 is a schematic illustration of thedynamic manufacturing and field issues feedback engine incorporating anoptimized order configurator of FIG. 3. Manufacturing and field issuesanalysis module 410 can be coupled to a manufacturing and field issuesdata store 140 that can include data associated with issues arisingduring the manufacturing process and arising from products installed andused in the field including a test case selection 420, rules for thetest case selection 435 and test case object information 440. Issueanalysis object information 340 can be coupled to the fieldmanufacturing and field issue analysis module 410 and the partsselection rule modifier 330.

The optimized order configurator 320 can include an order configurationengine 445 and a parts selection module 415 containing rules for partsselection 430, and parts object information 425. The parts selectionrule modifier 330 can have computer code enabled to update orderconfigurations by incorporating the issue analysis object information340 which can indicate non-reliable parts and/or part combinations andcontain type of issue or failure, and root causes corresponding to apart or product. The parts selection rule modifier 330 is a “rule-based”logic. The generic rules of the parts selection rule modifier 330 canmodify the relevant attributes of the parts used in the productconfigurations, so that when the optimized configurator 330 is appliedin future configuration orders, the problematic parts are appropriatelyeliminated or discouraged from use in future part selections, i.e.,product configurations. Some examples of the generic rules of the partsselection rule modifier 330 are illustrated and discussed with referenceto the table of FIG. 6 below.

By way of a user interface 450, the optimized order configurator 320 caninclude a configuration engine 445 that can be enabled to take theupdated parts object information 425 and rules modified by the partsselection rule modifier 330 and configure a product order byincorporating the rules for parts selection 430 and parts objectinformation 425. Thus after collecting product issues data, e.g.,manufacturing and field issue data, for a manufactured product, theparts selection rule modifier 330 can modify or tune the orderconfigurator to account for the characteristics in the collectedmanufacturing and field issue data, and apply the order configurator tothe next product order.

Consequently, the configured product order 220 can be accomplished bydynamically modifying the part object attributes or elements, andremoving or eliminating those parts and/or part combinations that failmore often based on dynamic manufacturing and field issue feedback.

In further illustration, FIG. 5 is a block diagram illustratingattributes of the parts object information and manufacturing and fieldissues object information in FIG. 4. The parts object information 425can have updated attributes that are relevant for establishing therelationship to the issue analysis objects information 340. Therelationship of an issue analysis object 340 to parts object 425 can be1 to N. Each issue analysis object 340 can represent the informationgathered from manufacturing and field issues reported.

The issue analysis object 340 will have attributes typicallyrepresenting the type of issue, e.g., a failure, and context of theissue. For example, such attributes can include an issue ID 550 thatidentifies a particular issue from the manufacturing and field issueanalysis. Other attributes may be affected parts 555, affected products560, an underlying root cause 565, e.g., “bad component”, “degradedcomponent”, “bad connection” or “bad interface” and an issue'senvironment 570, such as voltage, humidity, dust and number of cycles,among other attributes 575. The parts selection rule modifier 330 canprovide a relationship between the parts objects 425 and the issueanalysis objects 340 in order to create new rules or modify existingrules for parts selection. The part objects can have several attributesincluding but not limited to, part ID 500, applicable products 505,pre-requisites 510, co-requisites 515, preferences 520 such as“application” and “customer”, “Can Not Work With” 525, field environment530 such as “number of cycles”, “voltage”, “dust” and “humidity”, andapplication 535 among other attributes 540.

In further illustration, FIG. 6 is a table containing examples of rulesused to modify order configuration rules. The first modifier rule statesthat if a specific part is failing only in one or two products, removethese products from the Applicable Products list 505 attribute of thatpart's object information 425. For example, a component part “3N5427”fails in 9 of 9 occurrences. The failures occur in two products, e.g.,product “6335” and product “7509”. There are no associated parts withthe failing part “3N5427”. This information can be dynamically feedbackto the part selection rule modifier 330, which applies a set of “metarules/logic” such as the first rule of the table in FIG. 6. In thisexample, the course of action is to update the Applicable Product listattribute 505 to remove products “6335” and “7509”, and thereby insurethat part “3N5427” is no longer selected for use in products “6335” and“7509”.

The second modifier rule of the table in FIG. 6 states that if a part isfailing in all products but only when used with certain other partsand/or products, modify the “Can Not Work With” list attribute of thisapparently invalid combination of parts to include the certain part orparts that are causing the failure of the first part. In addition, anyrelated pre-requisites or co-requisites attributes should be modified ifthe problem parts and/or products appear in the pre-requisites orco-requisites attribute lists. For example, a component part “5T3333”fails in 7 of 7 occurrences. The failures occur in one product, e.g.,product “4436”. Part “6R8756” is associated with the failing part“5T3333”. This information can be dynamically feedback to the partselection rule modifier 330, which applies a set of “meta rules/logic”such as the second rule of the table in FIG. 6. In this example, thecourse of action is to update the Can Not Work With list attribute 525to include part “6R8756”, and thereby insure that part “6R8756” is nolonger selected for use in combination with part “5T3333” in futureconfigured orders.

In still further illustration, FIG. 7 is a flowchart illustrating aprocess for the parts selection rule modifier 330 using the dynamicmanufacturing and field issues feedback data. Beginning in block 705,manufacturing and field issues for manufactured products can be observedand collected for analysis 410, feedback to parts selection rulemodifier 330 and/or manufacturing and field issues storage 140. In block710, the parts that have the greatest number of manufacturing and fieldissues, e.g., those parts that fail most often, are separated from thoseparts that never or rarely have manufacturing and field issues. Theparts identified as having the greatest number of manufacturing andfield issues can be processed in block 715. The processing of theseidentified parts can include generating an issues analysis objectinformation 340 for each corresponding manufacturing and field issuecollected.

In decision block 720, it can be determined whether the identifiedcomponent only fails in certain products. If so, the identifiedcomponent's applicable products list is updated to remove the productsin which the identified component has issues or fails. Otherwise, thepreference attribute of the identified component can be modified toreduce its priority or even disable its use altogether, e.g., remove thepart from the “available” list and/or place the part on an “exclusion”list of the optimized configurator 320 in block 725. In block 735,associated parts of the identified problem part can be determined. Forexample, the identified problem part is part number “5Y3421” and itspre-requisite (or co-requisite) part is “6J7869”. In decision block 740,it can be determined if there are any equivalent parts to part number“5Y3421”, and if so, in block 750, the equivalent part (e.g., partnumber “5Y3422”) can be used to replace part number “5Y3421” in thepre-requisite (or co-requisite) attribute list of part number “6J7869”.Otherwise, pre-requisite (or co-requisite) part number “6J7869” can beremoved from the product configuration by reducing its priority or evendisabling its use altogether, e.g., remove the part from the “available”list of the optimized configurator 320 in block 745.

In an effort to improve product reliability and availability, in block755, the process can future include determining if there are any partsavailable that have a lower failure rate, which could be used instead ofthe equivalent parts identified in decision block 740. If so, indecision block 760, the priority attribute of the part having a lowerfailure rate is checked and if it is determined that its priority is notset to the highest level, then its priority is increased in block 765.

Finally, in decision block 770, it can be determined if additional partsremain to be processed. If so, the process can continue in block 715 asbefore. Otherwise, the process will stop in block 775.

The present invention can be realized in hardware, software, or acombination of hardware and software. An implementation of the methodand system of the present invention can be realized in a centralizedfashion in one computer system or in a distributed fashion wheredifferent elements are spread across several interconnected computersystems. Any kind of computer system, or other apparatus adapted forcarrying out the methods described herein, is suited to perform thefunctions described herein.

A typical combination of hardware and software could be ageneral-purpose computer system with a computer program that, when beingloaded and executed, controls the computer system such that it carriesout the methods described herein. The present invention can also beembedded in a computer program product, which comprises all the featuresenabling the implementation of the methods described herein, and which,when loaded in a computer system is able to carry out these methods.

Embodiments of the invention can take the form of an entirely hardwareembodiment, an entirely software embodiment or an embodiment containingboth hardware and software elements. In a preferred embodiment, theinvention is implemented in software, which includes but is not limitedto firmware, resident software, microcode, and the like. Furthermore,the invention can take the form of a computer program product accessiblefrom a computer-usable or computer-readable medium providing programcode for use by or in connection with a computer or any instructionexecution system.

For the purposes of this description, a computer-usable or computerreadable medium can be any apparatus that can contain, store,communicate, propagate, or transport the program for use by or inconnection with the instruction execution system, apparatus, or device.The medium can be an electronic, magnetic, optical, electromagnetic,infrared, or semiconductor system (or apparatus or device) or apropagation medium. Examples of a computer-readable medium include asemiconductor or solid state memory, magnetic tape, a removable computerdiskette, a random access memory (RAM), a read-only memory (ROM), arigid magnetic disk and an optical disk. Current examples of opticaldisks include compact disk-read only memory (CD-ROM), compactdisk-read/write (CD-R/W) and DVD.

Computer program or application in the present context means anyexpression, in any language, code or notation, of a set of instructionsintended to cause a system having an information processing capabilityto perform a particular function either directly or after either or bothof the following a) conversion to another language, code or notation; b)reproduction in a different material form. Significantly, this inventioncan be embodied in other specific forms without departing from thespirit or essential attributes thereof, and accordingly, referenceshould be had to the following claims, rather than to the foregoingspecification, as indicating the scope of the invention.

A data processing system suitable for storing and/or executing programcode will include at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements can includelocal memory employed during actual execution of the program code, bulkstorage, and cache memories which provide temporary storage of at leastsome program code in order to reduce the number of times code must beretrieved from bulk storage during execution. Input/output or I/Odevices (including but not limited to keyboards, displays, pointingdevices, etc.) can be coupled to the system either directly or throughintervening I/O controllers. Network adapters may also be coupled to thesystem to enable the data processing system to become coupled to otherdata processing systems or remote printers or storage devices throughintervening private or public networks. Modems, cable modem and Ethernetcards are just a few of the currently available types of networkadapters.

1. A method for dynamically tuning order configurator performance, themethod comprising: collecting product issue data for a manufacturedproduct, the product issue data including performance and attributeinformation of a part of the manufactured product; analyzing in anoptimized order configurator executing in memory by a processor of acomputer the collected product issue data to identify a problematicpart; and, modifying the order configurator using the analyzed productissue data, wherein the modifying the order configurator using theanalyzed product issue data further comprises modifying an existing partselection rule by removing the problematic part from an availabilitylist of the manufactured product.
 2. The method of claim 1, furthercomprising deploying the manufactured product in a location selectedfrom the group consisting of (i) a manufacturing facility and (ii) afield deployment.
 3. The method of claim 1, wherein the modifying theorder configurator using the analyzed product issue data comprisesadding a new part selection rule.
 4. The method of claim 1, wherein themodifying the order configurator using the analyzed product issue datacomprises modifying an attribute of the problematic part to avoidrepeating a current product configuration.
 5. The method of claim 4,wherein the modifying an attribute of the problematic part comprisesremoving the manufactured product from an applicable products list ofthe problematic part.
 6. A product issues data processing systemcomprising: a product issues data store; a product issues analysismodule coupled to the product issues data store and executing in memoryby at least one processor of a computer; an automated product issuesfeedback engine coupled to the product issues analysis module, theproduct issues feedback engine comprising program code enabled tocollect product issues data for a manufactured product, the productissues data associating characteristics of the manufactured productdetermined to have issues during manufacturing and field deployment, tomodify an existing configuration order for the manufactured product toaccount for the characteristics in the collected product issues data;wherein the product issues feedback engine further comprises: issuesanalysis object information; a parts selection rule modifier coupled tothe issues analysis object information wherein the parts selection rulemodifier comprises program code enabled to dynamically change prioritiesof parts, the applicability status of parts, and to selectively enableor disable parts; and an optimized order configurator coupled to theparts selection rule modifier, the order configurator comprising rulesfor parts selection and parts object information and the parts selectionrule modifier comprising program code enabled to dynamically changepriorities of parts, the applicability status of parts, and toselectively enable or disable parts.
 7. The system of claim 6, whereinthe program code is further enabled to apply the modified configurationorder to the manufactured product.
 8. The system of claim 6, wherein theproduct issues analysis object information comprises a collection ofroot cause analysis information.
 9. A computer program productcomprising a computer usable storage medium embodying computer usableprogram code for generating product issue feedback, the computer programproduct comprising: computer usable program code for collecting productissue data for a manufactured product, the product issue data includingperformance and attribute information of a part of the manufacturedproduct; computer usable program code for analyzing the collectedproduct issue data to identify a problematic part; and computer usableprogram code for modifying the order configurator using the analyzedproduct issue data, wherein the computer usable program code formodifying the order configurator using the analyzed product issue datacomprises modifying an existing part selection rule by removing theproblematic part from an availability list of the manufactured product.10. The computer program product of claim 9, wherein the computer usableprogram code for modifying the order configurator using the analyzedproduct issue data comprises adding a new part selection rule.
 11. Thecomputer program product of claim 9, wherein the computer usable programcode for modifying the order configurator using the analyzed productissue data comprises modifying an attribute of the problematic part toavoid repeating a current product configuration.
 12. The computerprogram product of claim 11, wherein the computer usable program codefor modifying an attribute of the problematic part to avoid repeating acurrent product configuration comprises removing the manufacturedproduct from an applicable products list of the problematic part.